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        <td class="header">&nbsp; Principal Component
            Analysis
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<h3>Principal Component Analysis Operator</h3>

<p>This operator generates the principal component images from a
    stack of
    co-registered detected images.
    &nbsp;The Principal Component Analysis (PCA) consists of a
    remapping of
    the information of the input co-registered images into a new set of
    images. &nbsp;The output images are scaled to prevent negative
    pixel
    values.</p>
<h4>Major Processing Steps<br></h4>

<p>
    The PCA operator consists of the following major steps:</p>
<ol>
    <li>
        <p>Average the pixels across the input images to compute a
            mean image. Optionally subtract the computed mean image from each input image.</p>
    </li>
    <li>
        <p>Subtract the mean value of each input image (or image from
            step 1) from itself to produce zero-mean images.</p>
    </li>
    <li>
        <p>Compute covariance matrix from the zero-mean images given
            in step 2.</p>
    </li>
    <li>
        <p>Perform eigenvalue decomposition of the covariance matrix.</p>
    </li>
    <li>
        <p>Compute
            PCA images by multiplying the eigenvector matrix by the zero-mean
            images given in step2. Here the user can select the eigenvectors
            instead of using all vectors. The selection is done with a user input
            threshold, which is in percentage, on the eigenvalues. For example, in
            the case of three input images, a1, a2 and a3 (where a1 >> a2 >>
            a3) are the eigenvalues, if the threshold is 80% and (a1+a2) >> 80%,
            then a3 will not used in computing the PCA images.&nbsp;Only two PCA images will be produced.</p>
    </li>
</ol>
<h4>Parameters Used<br></h4>

<p>
    The following parameters are used by the operator:
</p>
<ol>
    <li>
        <p> Source Bands:&nbsp;All bands (real or virtual) of the source
            product. You may select one or more bands for performing PCA. If no
            bands are selected, then by default all bands will be selected.<br></p>
    </li>
    <li>
        <p> Eigenvalue Threshold: The threshold used in the
            eigenvalue selection for producing the final PCA images.
        </p>
    </li>
    <li>
        <p> Show eigenvalues: Checkbox indicating that eigenvalues
            are displayed automatically.
        </p>
    </li>
    <li>
        <p> Subtract Mean Image: Checkbox indicating that the mean
            image
            of user selected input images will be subtracted from each input image
            before&nbsp;Principal Component Analysis is applied.</p></li>
</ol>
<img style="width: 500px; height: 411px;" alt="" src="images/pca_dlg.jpg"><br><br><br>
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